Triple

T6923819
Position Surface form Disambiguated ID Type / Status
Subject Sault Ste. Marie Airport E160253 entity
Predicate hasRunway P105 FINISHED
Object Runway 12/30
Runway 12/30 is a primary paved runway at Sault Ste. Marie Airport in Ontario, Canada, used for regional and commercial air traffic operations.
 E690894 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Runway 12/30 | Statement: [Sault Ste. Marie Airport, hasRunway, Runway 12/30]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 12/30
Context triple: [Sault Ste. Marie Airport, hasRunway, Runway 12/30]
  • A. Runway 12/30
    Runway 12/30 is the primary paved runway used for commercial flight operations at L.F. Wade International Airport in Bermuda.
  • B. Runway 12/30
    Runway 12/30 is a primary paved runway at San Carlos Airport in California, used mainly for general aviation operations.
  • C. Runway 12/30
    Runway 12/30 is a primary paved runway at Albuquerque International Sunport used for commercial and general aviation takeoffs and landings.
  • D. Runway 12/30
    Runway 12/30 is a principal runway at Cairns Airport in Queensland, Australia, used for both domestic and international aircraft operations.
  • E. Runway 12/30
    Runway 12/30 is a primary paved runway at Edmonton International Airport used for handling a wide range of commercial and general aviation traffic.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Runway 12/30
Triple: [Sault Ste. Marie Airport, hasRunway, Runway 12/30]
Generated description
Runway 12/30 is a primary paved runway at Sault Ste. Marie Airport in Ontario, Canada, used for regional and commercial air traffic operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 12/30
Target entity description: Runway 12/30 is a primary paved runway at Sault Ste. Marie Airport in Ontario, Canada, used for regional and commercial air traffic operations.
  • A. Runway 12/30
    Runway 12/30 is a primary paved runway at Edmonton International Airport used for handling a wide range of commercial and general aviation traffic.
  • B. Runway 12/30
    Runway 12/30 is a primary paved runway at Albuquerque International Sunport used for commercial and general aviation takeoffs and landings.
  • C. Runway 12/30
    Runway 12/30 is a principal paved runway at Canberra Airport used for handling domestic and international air traffic.
  • D. Runway 12/30
    Runway 12/30 is a primary paved runway at San Carlos Airport in California, used mainly for general aviation operations.
  • E. Runway 12/30
    Runway 12/30 is one of the primary paved runways used for aircraft takeoffs and landings at Washington Dulles International Airport in Virginia.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c6884d350081908d8a970e4d40ad78 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d9fea8d08190b6099a24fbac7de5 completed March 27, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c95675f24c81909f9c14e29a79c157 completed March 29, 2026, 4:42 p.m.
NEDg Description generation batch_69c95a4e0fd8819099da4b3f3ced733c completed March 29, 2026, 4:58 p.m.
NED2 Entity disambiguation (via description) batch_69c95aa66a6c819091116c4b83082dd9 completed March 29, 2026, 5 p.m.
Created at: March 27, 2026, 2:26 p.m.